cbazzaandClaude Opus 4.5
d25727839a
- Add signal_cache.py module to persist signal data between trade open/close - Modify execute_trade_v2_adaptive to cache signal info when trade opens - Update sync_closed_trades_to_tracker to retrieve cached ML features - Update scheduled_demo_tracker_sync with same ML feature retrieval This enables proper ML training by capturing: - base_confidence, enhanced_score, hybrid_score - signal_quality, market_regime, regime_strength - session and lot_multiplier Previously all trades were logged with 0 values for ML features. After ~50-100 new trades, the ML model can be properly trained. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>